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Assessing the internal consistency and temporal stability of advance directives generated by an interactive, online computer program
  1. Jane R Schubart1,
  2. Fabian Camacho2,
  3. Michael J Green3,
  4. Kimberly A Rush4 and
  5. Benjamin H Levi5
  1. 1Departments of Surgery, Public Health Sciences, and Medicine, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvania, USA
  2. 2Department of Public Health Sciences, University of Virginia, School of Medicine, Charlottesville, Virginia, USA
  3. 3Departments of Humanities and Medicine, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvania, USA
  4. 4Department of Pediatrics, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvania, USA
  5. 5Departments of Humanities and Pediatrics, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvania, USA
  1. Correspondence to Dr Jane R Schubart, Departments of Surgery, Public Health Sciences, and Medicine, The Pennsylvania State University, College of Medicine, 500 University Drive, Hershey, PA 17033, USA; jschubart{at}hmc.psu.edu

Abstract

Objective Evaluate the internal consistency and temporal stability of advance directives (ADs) generated by an interactive, online computer program.

Methods 33 participants completed the program at three visits, 2 weeks apart. Agreement rates were calculated for the General Wishes component of the AD. The test–retest method was used to examine the temporal stability of the Specific Wish for Treatment component which contains five clinical scenarios.

Results General Wishes remained stable with 94% selecting the identical response at each visit. For the Specific Wish for Treatment scale, significant variations in test–retest correlations existed (ie, ρ=0.32–0.78, between time points 1 and 2); however within scenario, correlations did not significantly vary between time points. Temporal stability was lower in the Specific Wish for Treatment scale compared with General Wishes (average ρ=0.59, between time points 1 and 2; and ρ=0.75, between time points 2 and 3).

Conclusions ADs generated by an online decision aid demonstrate good temporal stability, with highest stability for General Wishes and moderate stability for Specific Wish for Treatment regarding medical treatments in specific clinical scenarios. Internal consistency for wish for treatment across all time points and scenarios was high (Cronbach α>0.90).

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  • Received 3 November 2014.
  • Revision received 7 January 2015.
  • Accepted 17 February 2015.
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